Database & API Development — The Backend Layer Your Product Depends On

Database development is the design of how your data is stored — schema, indexes, partitions, relationships, and access patterns. API development is the design of how that data is exposed — the endpoints, contracts, authentication, and integration semantics that other applications use to interact with your system. The two are deeply connected: a poorly modelled database makes every API on top of it slower and harder to maintain, and a well-modelled database gives every API a faster path to ship. We typically do both together because the architecture decisions for one shape the other.

Both — driven by the consumer profile and access patterns, not by personal preference. REST is the right choice for predictable resource models, public APIs, and integrations where caching and HTTP semantics matter. GraphQL is the right choice when frontend teams need flexible queries that reduce over-fetching, or when a single API serves multiple frontends with different data requirements. We help you pick the right one during scoping rather than defaulting to one because it is fashionable.

Node.js with TypeScript is our default for API and backend work. We work with PostgreSQL, MySQL, MongoDB, DynamoDB, and Firestore for databases; Supabase and Firebase for managed backend services where they fit the workload; Stripe, HubSpot, Salesforce, Mailchimp, and Twilio for common integrations; and AWS, Azure, Google Cloud, and DigitalOcean for cloud infrastructure. We pick technology based on what your application actually needs — not on which platform pays better commission.

Yes — third-party integrations are a significant portion of what we build. Stripe and Stripe Connect for payments and subscriptions, HubSpot and Salesforce for CRM sync, Mailchimp and ActiveCampaign for marketing automation, Twilio for SMS, Slack for team notifications, and bespoke API integrations across whatever stack you run. Every integration we build includes idempotency, retry logic, signed webhook verification, dead-letter handling, and reconciliation jobs — so silent failures become impossible.

Yes. Real-time features are built on WebSocket, Server-Sent Events, or Pusher/Ably/Supabase Realtime depending on the workload. We design real-time architecture around the actual update patterns — broadcast updates differ from per-user channels, and high-frequency telemetry differs from human chat. The choice of transport, fan-out strategy, and presence handling are all decisions made during scoping rather than left as default.

Authentication is built around your audience. OAuth 2.0 and JWT for API consumers, session-based auth for web users where it suits the deployment model, SSO with Google, Microsoft, and SAML for enterprise SaaS plans, and refresh-token rotation handled correctly so security audits don't surface basic mistakes. Authorisation is implemented as proper role-based or attribute-based access control with the rules expressed once rather than scattered across endpoints — and audit logging is configured by default for any system that will eventually face an SOC 2 or ISO 27001 review.

Yes — backends for iOS, Android, and React Native apps are a common project type. We design APIs with mobile in mind from the start: pagination strategies that work over slow networks, push notification integration, offline-first patterns where connectivity matters, and authentication that handles mobile-specific cases like secure enclave storage and biometric unlock. We coordinate with our app development team where the app is being built alongside the backend.

Yes. SaaS-specific backends typically need multi-tenancy (separate-schema, shared-schema with row-level security, or fully separate databases depending on customer profile), Stripe or Paddle subscription billing with proper trial, dunning, upgrade, downgrade, and cancellation flows, role-based access for teams and organisations, audit logging for compliance, and admin tooling so your support team can act without escalating to engineering. We design these for the boring multi-year reality of running a SaaS product — not just the demo path.

Both. New projects get full schema design starting from the domain model and access patterns — relational, document, key-value, or hybrid storage chosen by workload. Existing databases get audited (query plan analysis, index review, schema smell detection) and optimised with quantified before/after performance documentation. For systems where the existing schema is fundamentally limiting the product, we plan zero-downtime migration paths rather than living with the bottleneck indefinitely.

Yes. Data migrations are one of the highest-risk projects we run — and one of the most commonly mishandled. We approach migrations as engineering projects: source-to-target schema mapping, transformation rules, validation strategy (row counts, checksums, sampled comparisons), staged cut-over with private testing windows, and a rollback path that keeps the old system live until success criteria are met. Migrations between CRMs, eCommerce platforms, cloud databases, and SaaS systems are all routine for our team.

Backend work does not end at launch — it changes shape. Ongoing maintenance covers dependency and security patching, performance monitoring with regression detection, query and index review as data volume grows, integration health monitoring (especially webhook delivery and reconciliation), cloud cost optimisation, and the feature evolution that real products always need. Available as a fixed monthly retainer scaled to your system, or as ad-hoc support on a defined response SLA.

Yes. We build headless CMS implementations on Sanity, Strapi, and Payload — chosen by editor experience, content model complexity, and self-hosting requirements. Each project includes content modelling around your editorial workflow, role-based access for multi-team publishing, GraphQL or REST content APIs with CDN caching, and Next.js frontend integration with incremental static regeneration so content updates appear quickly without full site rebuilds.

Performance optimisation is evidence-based. We start with APM data and slow query logs to identify the queries and endpoints that actually matter, run EXPLAIN against the slow ones, and adjust index strategy, query structure, connection pooling, and caching layers against the real workload. Page-level optimisation includes proper pagination, response compression, and HTTP caching for endpoints that allow it. The improvement is measured and documented — not assumed.

Yes. We frequently extend or integrate with existing systems — Python, Ruby, PHP, .NET, Java, or whatever stack your business already runs. The work either takes the form of adding APIs in front of legacy systems (the strangler-fig pattern), integrating new services alongside existing ones, or migrating one piece at a time without a big-bang rewrite. We work with your stack rather than asking you to switch to ours.

Project pricing is scoped against agreed deliverables and complexity rather than per-hour. We produce a written quote covering the endpoints, data models, integrations, and success criteria — and the price holds for the agreed scope. For ongoing engagements (retainers for maintenance, integration support, or continued feature work), we offer fixed monthly retainers scaled to your codebase and release cadence. There are no surprise change orders for work that was always part of the scope.

Most single API integrations start from around £600 and a typical multi-system integration project sits in the £1,500–£6,000 range, depending on complexity. A clean, well-documented third-party API like Stripe Checkout is at the lower end. Costs rise when the integration needs bi-directional sync (HubSpot or Salesforce), idempotency and reconciliation to handle duplicate or out-of-order events, signed webhook verification, and dead-letter handling for failures. Poorly documented or legacy APIs add discovery time. We scope each integration in writing against the endpoints, data mapping, and failure modes involved, so the quote reflects the real work rather than a guessed flat rate — and the price holds for the agreed scope.

As a rule of thumb, you have outgrown off-the-shelf software once you are paying for three or more disconnected tools and still exporting spreadsheets to bridge them. Off-the-shelf platforms suit standard, well-understood processes — accounting, generic CRM, basic stock control. A custom database becomes worth it when your data model is genuinely specific to how you operate, when per-seat or per-record SaaS pricing scales painfully against your growth, or when you need integrations and reporting the off-the-shelf tool will not expose. Custom database development costs more upfront but removes recurring licence fees and the operational drag of manual workarounds. We help you make that call honestly during scoping — sometimes the right answer is configuring an existing tool, not building.

Yes — CRM and payment integrations are among the most common projects we deliver, and a well-built one usually pays for itself within 6–12 months in saved admin time. On payments we work with Stripe, Stripe Connect, GoCardless, and PayPal for one-off charges, subscriptions, and marketplace flows. On CRM we build bi-directional sync with HubSpot, Salesforce, and Pipedrive so leads, deals, and contacts stay consistent across systems without manual re-keying. Every integration ships with idempotency, retry logic, signed webhook verification, and reconciliation jobs, so a dropped event or duplicate charge cannot quietly corrupt your data. We map the fields, agree the sync direction, and test the failure cases before launch.

Security is built in from the first architecture decision, not bolted on before launch. The baseline on every project includes encryption in transit (TLS) and at rest, secrets held in a managed vault rather than environment files, role-based or attribute-based access control, and audit logging. For UK GDPR specifically, we support data minimisation in the schema, configurable retention and deletion to satisfy the right to erasure, export endpoints for subject access requests, and data residency in UK or EU regions when your obligations require it. We also lay the foundational controls needed for an eventual ISO 27001 or SOC 2 review. Where you process special-category data, we document the data flows so your DPIA has something concrete to reference.

Most custom database and API projects take 4–12 weeks from kick-off to launch, with the variation driven by integration count and data complexity rather than raw size. A focused build — one well-modelled database plus a REST or GraphQL API — typically lands in 4–6 weeks. Multiple third-party integrations, real-time features, multi-tenancy, or a data migration from an existing system push timelines toward 8–12 weeks. We front-load architecture and data modelling so estimates firm up early, and we deliver in milestones you can review rather than a single big-bang release. Data migrations add a staged cut-over window with a rollback path, since rushing those is where most projects go wrong.